Left: "Initial image" VS Right: result "imagined".
I will also explain step by step how you can try yourself! Your head will blow up 🤯
1. Super Mario.
More 🧵👇
2. Guybrush Threepwood.
3. Wizzard.
4. Cute girls.
5. Sonic with ugly hands 😂 (is a work in progress for AIs).
6. Charmander (from "love you I'm cute" to "I will finish you").
7. Fez map (several versions).
8. Link.
9. Peach (well... more or less, hahaha).
10. Donkey Kong.
11. Eastward.
I was surprised by how beautiful the whale has turned out.
Disclaimer! with this experiment I'm not saying that the new images are better. In fact, #pixelart drives me crazy and many of the original images transmit a lot more to me.
I'm just exploring the potential of this tech. Something like this has so many potential applications.
12. Tales of Phantasia.
Even more difficult: not only pixelated, but also blurry. The mask is a cool addition 🤣
13. Thimbleweed Park.
14. Day of the Tentacle.
15. This is interesting: pixelated avatar of my friend.
Here we can see how the AI, having been trained with 5000M images, generates a bit of what it wants (the information is invented).
Of course: none of them look like him in real life 🤣
And well, the AI has done a little what it wanted, as always, hahaha. I forgot to describe that the bottom thing was a bear. I only put "dinosaurs". And of course, this is what happened.
4/ Then, use a prompt like this: "[a detailed description of what you want], highly detailed, smooth, sharp focus, 8k, ray tracing, digital painting, concept art illustration, by artgerm, trending on artstation, nikon d850".
5/ Important! You will have to play with "Image Strength". The sweet point is around 25%-35%
6/ Important! You will have to play with "Cfg Scale" too. The trick is to use a high value around 16-20.
7/ Be patient! Lot of times you will have to cherry pick a good result after lot of trying. Usually they are bit... monstrous.
8/ By the using the "seed number" (for the Mario example I used 4128836123 and StableDiffusion 1.5) you can iterate over a promising image by "anchoring" it with the seed.
Hey, @EMostaque thanks a lot for SD! It is REALLY useful. I also tried with your avatar 😊
Hope u liked this thread!
Would you like to learn more about AI image generation?
🔥 Follow me! 🔥
I'm working on a prompts bundle I will release soon, with detailed explanations to be able to create awesome images! It will include the MOST ADVANCED prompts I found.
If you liked this thread, a RT to the first tweet of the thread will encourage me to keep posting, thanks! 🙏👇
This is a side of me I don’t usually share publicly: my investment thesis based on my vision of the future. Because investing is exactly that: a bet that we’ll be able to guess the future.
Go grab a coffee, ‘cause this one’s gonna be long. It’s been a while since I put this much effort into a thread:
1. 🔮 My predictions.
• AI and everything that supports it (GPUs, datacenters, etc) will keep growing exponentially and steadily over the coming years, impacting every field of human knowledge.
• In the near future, every work process that happens in front of a computer will be affected by AI (if not completely swept away). And soon after that, every process that happens away from a computer too, thanks to robotics. And when AI and robotics converge, we’re in for some very interesting times (hopefully not terrifying).
• Pay close attention to what I’m about to say, it might blow your mind: I believe software (and a big chunk of audiovisual entertainment) will become a commodity, like electricity. Which means all the digital tech value will be concentrated in just a few companies: those who win today’s multimodal LLM race and those who provide the infrastructure they run on. You might understand this better if you imagine a world where you can just say: “I want a SaaS like this site” or “make me a movie in this style with my dog as the main character” and an LLM creates it on the spot, with a quality far beyond today’s best productions. Basically, I believe all logic and visual layers will be run on advanced LLMs we can barely imagine today. So, building apps/webs/entertainment the way we do now will stop making sense, and the ability to do so will be concentrated in companies with the best LLMs and the compute power to run them at scale. We’ll choose between “AI providers” based purely on price, and not so much on features/capabilities (just like we do today with electricity companies; or like PS vs Xbox if they get some exclusive IPs that make a difference).
2. 💰 My general investment thesis.
• There will be investment opportunities in everything that drives this paradigm shift (AI itself), but also in things that will still exist with or without AI (like food, real estate, or tourism (though I won’t cover these here, even if they’re still interesting and I might invest in them outside the stock market).
• As for AI, I’ll invest in both the “gold hunters” 🥇 (the companies in the race to build the foundation models) and the ones selling picks and shovels ⛏️ (the companies building the hardware and infrastructure that make AI possible).
• Trying to “time the market” to find the perfect entry point is impossible. But there are some strong signs that the market is currently overvalued (see attached screenshot, data from CurrentMarketValuation).
• Concentrating your investment increases potential return, but also the risk. And vice versa.
3. 💸 My specific investment thesis.
• I want very high concentration in AI companies and everything that supports it, both in pre-IPO and in public markets.
• I think not only the US, but also China, will play a huge role in AI’s future. I have less faith in my dear Europe, because of its obsessive regulatory spiral and its ink-stained bureaucrats. Yes, I believe the US and China will devour the AI pie. But with China I sadly assume regulatory risks, so I won’t go above 10%-20% exposure in my portfolio.
• I don’t want to go all in at once in case the market is, in fact, overvalued: so I’ll be investing through monthly/quarterly contributions (TBD) over the next 5-6 years. In other words, I’ll avoid Lump Sum and follow a DCA (Dollar-Cost Averaging) strategy. This also lets me easily tweak the strategy later through future contributions if my portfolio drifts off course. Detail: historically, Lump Sum performs better... except when you hit the market at its peak. And since all signs point to us being maybe too high right now, I don’t want to risk it.
• But I don’t do trading. I actually DON’T believe in trading. Over 90% of active traders underperform the market in the long run. Even professional fund managers can’t consistently beat a simple index like the S&P 500 or MSCI World. So my plan is to build the portfolio over time, according to the weights in the screenshot, and never sell (unless I ever really need the cash). If anything, if I see the market drop hard, I’ll “buy the dip” and invest 2x or 3x the regular amount to take advantage of the discounts.
• Related to the above: author funds and picking individual stocks usually perform worse on average than simply indexing. So I want at least 70% of my portfolio to be indexed. But I’ll trust my own judgment and pick a few individual ones (30% of the portfolio). Again, I’m not planning to buy and sell often, just enter regularly over time.
• TER (fees) of funds and ETFs are super important and should be studied carefully. If not, they’ll eat you alive long-term. I’ve looked for the best products that match my thesis, but also the cheapest ones.
• I prefer accumulation over distribution for tax efficiency (I want at least 75% of my portfolio in accumulation stocks/ETFs). Long live compound interest!
• In Spain, moving between funds doesn’t trigger taxes (until you sell). The only downside is that fees are several points higher. But I want to keep at least a portion in funds so I can move things around easily and tax-free if needed.
• I think some of the best opportunities aren’t in public markets, but in pre-IPOs. I’ve managed to get into OpenAI, xAI, SpaceX, Freepik and Canva. I’d love to get into Anthropic, Inflection AI, Cohere, Hugging Face, Cerebras and Midjourney if I ever get the chance. If the stock market is already risky, the barrier to entry and risk for pre-IPOs or startups is way higher.
4. 🤯 Key risks to keep in mind.
• If you run this investment thesis through Gemini, Grok or ChatGPT’s deep research mode, their heads will explode 😂 (yep, I’ve tried them all, of course, I actually built this AI-focused portfolio partly using AI). Any LLM will lose its mind over the extreme AI concentration in this portfolio. If you concentrate, you increase risk but also potential return. If you diversify, you reduce risk but also reduce returns. I chose the former and I’m okay with the risks.
• “IE00BLRPRL42 (similar to TQQQ but accumulation)”: not for the faint of heart. It’s leveraged 3x, can go up fast... but also vanish at the speed of light.
• Cathie Wood’s ARKs are risky by nature. “Author ETFs” tend to underperform index funds, so they’re a risky bet on extreme concentration.
• KSTR is a Chinese AI companies ETF. Many are opaque, government-dependent, and vulnerable to sanctions or bans.
• The fact that I chose to enter gradually (DCA) means I’ll need to stay alert and rebalance in the future, sell duds before they crash and keep an eye especially on author ETFs and individual stocks. No one wants a 3dfx or a BlackBerry in their future portfolio... but it’s sooo easy to end up with one!
5. 🦄 Disclaimer: this is *definitely* not investment advice.
These are just my personal predictions about the future (which I might totally get wrong, because predicting the future is nearly impossible) and my investment thesis based on those predictions, which I decided to share. You’d be nuts to take this as investment advice. Everyone should make their own decisions.
So... how’s your brain doing after all that? Can’t wait to hear your thoughts!
Just reply with your own image of the next frame you imagine.
I’ll be selecting the images and adding them to the thread so you’ll know what’s “canonical story”.
Finally, I’ll interpolate all the frames into a full video. Let’s see where this goes!
Style: "Retro tech-noir anime, like Akira, Ghost in the Shell, or Cyber City Oedo 808: cool tones and neon lights, strong shadows, intense expressions, and a futuristic, dark, and dramatic atmosphere."
Generate any image controlling structural integrity ✨ Infinite use cases! Films, 3D, video games, art, interiors, architecture... From cartoon to real, the opposite, or ANYTHING in between!
The VFX team of Here (directed by Robert Zemeckis and starring Robin Wright & Tom Hanks) used Magnific for their FX 🤯
To break it all down (+more), I interviewed VFX supervisor Kevin Baillie! 🧵👇
An incredibly exciting conversation where @kbvfx shares how he got started in the world of VFX, his career journey, what it’s been like working with directors like George Lucas and Robert Zemeckis, and the impact of generative AI in Hollywood plus much more!
So happy to finally be able to share the details!
I've been biting my nails for months but we weren’t allowed to make it public until NOW. Huge thanks to Kevin, finally!
As a co-founder of Magnific, seeing our creation used in a film directed by Robert Zemeckis (Back to the Future, Forrest Gump, etc.) is a dream come true.
We've always known that Magnific is a tool used by professionals (Dior, MrBeast, Adobe, Beeple, etc.), but seeing something this incredible with our own eyes makes it all feel so much more real.
You have no idea how happy this has made me. I don’t think I’ve felt this proud since that one time, by some miracle, I beat Emilio at Age of Empires.
Anyway, I won’t ramble on. Here are the questions Kevin was kind enough to answer, you won’t want to miss them!
Today, I’m going to talk about something we might be able to achieve, though maybe humanity should never even try:
A method for an AI to gain consciousness and reach the status of a superintelligence (ASI).
A theory I’ve been working on for months 🧵
Index – In case you want to jump straight to a section:
0️⃣ Introduction
1️⃣ The foundation of current AI models
2️⃣ What is consciousness?
3️⃣ How to create a self-aware AI?
4️⃣ Singularity / ASI
5️⃣ Moral implications
6️⃣ Risks
0️⃣ Introduction
I’ve been thinking about this idea for a long time, slowly working through its foundations.
Let me start by saying I am NOT a researcher a this is NOT a paper. While I’ve been close to the theory behind foundational AI models, my knowledge has its limits.
The idea I’m about to share is ridiculously simple and it could be VERY wrong.
But what if, against all odds, it really IS as simple as what I’m proposing?
Criticize the idea, not the person: I’d love to hear your thoughts and debate. Thanks!